At a Glance
- Tasks: Develop and maintain a cutting-edge asset simulation platform using Python and C++.
- Company: Global asset manager based in London, focused on innovation and excellence.
- Benefits: Competitive salary, professional development, and opportunities for career advancement.
- Other info: Collaborative environment with a focus on automation and scalability in research.
- Why this job: Join a dynamic team and make an impact in the world of finance and investment.
- Qualifications: Master’s degree in relevant fields and 3-5 years of quantitative experience required.
The predicted salary is between 60000 - 80000 € per year.
Responsibilities
- Develop, maintain and calibrate a proprietary asset simulation platform
- Model capital market assumptions and produce asset class simulations
- Design and implement macro-financial models in Python and/or C++
- Adapt internal models to specific optimisation and simulation requirements
- Build ad-hoc analytical tools in Python and Excel to deliver customised solutions
- Support Strategic Asset Allocation, ALM and lifecycle investing (including decumulation)
- Contribute to forecasts and portfolio construction best practice across geographies and asset classes
- Provide technical support to sales/clients and present methods and results clearly
- Write clean, tested code; use Git and deploy into production environments
- Drive automation and scalability across quantitative research processes
Requirements
- Master’s degree in Mathematics, Statistics, Computer Science, Economics or Financial Engineering
- 3–5 years’ experience as a quantitative analyst/programmer in an asset manager or investment bank
- Strong foundation in probability theory, stochastic calculus and statistical inference
- Experience modelling liquid and illiquid asset classes, asset allocation and portfolio optimisation
- Hands-on exposure to bond pricing, stochastic volatility modelling and Monte Carlo simulations
- Proficient in time-series analysis, econometrics and factor-based modelling
- Advanced Python (numpy, pandas); experience deploying code to production
- C++ a strong advantage; SQL proficiency; MS Office with VBA a plus
Quantitative Analyst/Quantitative Programmer, Global Asset Manager, London - eFinancialCareers employer: eFinancialCareers
As a leading global asset manager based in London, we pride ourselves on fostering a dynamic and inclusive work culture that encourages innovation and collaboration. Our employees benefit from comprehensive professional development opportunities, competitive compensation packages, and the chance to work on cutting-edge financial models that shape investment strategies worldwide. Join us to be part of a team that values your contributions and supports your growth in a vibrant city known for its financial prowess.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Analyst/Quantitative Programmer, Global Asset Manager, London - eFinancialCareers
✨Tip Number 1
Network like a pro! Reach out to professionals in the asset management field on LinkedIn or at industry events. We can’t stress enough how personal connections can lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and C++. We want to see your coding chops and how you’ve tackled real-world problems in quantitative analysis.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with asset simulations and macro-financial models. We recommend practising common interview questions related to probability theory and statistical inference.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Quantitative Analyst/Quantitative Programmer, Global Asset Manager, London - eFinancialCareers
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your expertise in Python, C++, and any relevant quantitative analysis you've done. We want to see how you can contribute to our asset simulation platform!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative analysis and how your background aligns with our needs. Don’t forget to mention specific projects or achievements that showcase your skills.
Showcase Your Technical Skills:Since we’re looking for someone with strong programming skills, make sure to include examples of your work with Python, C++, and any other relevant tools. If you’ve deployed code into production, let us know how you did it!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come in through our own channels!
How to prepare for a job interview at eFinancialCareers
✨Know Your Models Inside Out
Make sure you can discuss the macro-financial models you've designed and implemented. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This shows your depth of knowledge and problem-solving skills.
✨Showcase Your Coding Skills
Since the role requires advanced Python and possibly C++, be prepared to demonstrate your coding abilities. You might be asked to solve a problem on the spot or discuss your previous projects. Brush up on your coding practices and be ready to write clean, tested code.
✨Understand Asset Classes Thoroughly
Familiarise yourself with both liquid and illiquid asset classes, as well as portfolio optimisation techniques. Be prepared to discuss how you would model these assets and contribute to strategic asset allocation. This will show that you have the practical knowledge needed for the role.
✨Prepare for Technical Questions
Expect questions on probability theory, stochastic calculus, and statistical inference. Review key concepts and be ready to apply them to real-world scenarios. This will demonstrate your analytical skills and your ability to think critically under pressure.
